Triple
T273303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Looming Tower |
E5684
|
entity |
| Predicate | adaptationFormat |
P1926
|
FINISHED |
| Object | television miniseries |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: television miniseries | Statement: [The Looming Tower, adaptationFormat, television miniseries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationFormat Context triple: [The Looming Tower, adaptationFormat, television miniseries]
-
A.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
B.
adaptedAs
chosen
Indicates that one work, concept, or entity has been transformed or re-created into another form or medium based on the original.
-
C.
adaptedTo
Indicates that one entity has been modified, adjusted, or evolved to function effectively within the conditions, requirements, or characteristics defined by another entity.
-
D.
adaptation
Indicates a relationship where one entity changes or is modified to better suit, function within, or correspond to another entity or context.
-
E.
format
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dcf667c8190a7b8630fe67b9a90 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7345c4819086c21710864a1b42 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.